Abstract:

Research in substrate-based computing has shown that materials contain
rich properties that can be exploited to solve computational problems. One such
technique known as Evolution-in-materio uses evolutionary algorithms to manipulate
material substrates for computation. However, in general, modelling the computational
processes occurring in such systems is a difficult task and understanding
what part of the embodied system is doing the computation is still fairly ill-defined.
This chapter discusses the prospects of using Reservoir Computing as a model for
in materio computing, introducing new training techniques (taken from Reservoir
Computing) that could overcome training difficulties found in the current Evolution-in-Materio technique.